A method, system, apparatus, and medium for simulating aerodynamic force data for a near space vehicle

Abstract

The application discloses a method, system, device and medium for simulating aerodynamic force data of a near space vehicle, comprising: obtaining particles not participating in collision in a physical grid through a competition weight mechanism, and counting the number of particles not participating in collision flowing into adjacent physical grids to obtain flux of a particle solver; obtaining total flux between adjacent physical grids based on macro flux between the adjacent physical grids and the flux of the particle solver; updating physical quantities in the physical grid, obtaining flow field density based on the physical quantities in the physical grid; judging whether the flow field density obtained at an adjacent time step is less than a set threshold; and if yes, outputting a simulated flow field and a flow characteristic parameter. The application accurately simulates cross-flow problems existing in a flow field of a near space vehicle, simulates an aerodynamic shape of the near space vehicle and obtains aerodynamic force data of the near space vehicle, and solves the problem that existing simulation methods cannot consider both calculation efficiency and calculation accuracy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of fluid mechanics, and relates to a method, system, device and medium for simulating aerodynamic force data of a near-space vehicle. BACKGROUND

[0002] Compared with general aerodynamic simulation of a vehicle, the particularity of the simulation of a near-space (20km-100km) vehicle lies in the need to simulate rarefied flow. Under the condition of the near space, especially high altitude (70km and above), the incoming flow is relatively rarefied, and the ground wind tunnel test often cannot reproduce the incoming flow condition under the real flight condition. The method of flight test is too high in cost. The high-precision high-altitude aerodynamic force data are basically obtained by a numerical simulation method.

[0003] Since the rarefied flow does not satisfy the continuous medium assumption, the common Navier-Stokes method cannot simulate the rarefied flow, and therefore there are generally two types of simulation methods used in this field: the first type is an extended method of the continuous method, i.e., the Navier-Stokes method, which is improved on the basis of the Navier-Stokes method and is high in calculation efficiency but low in accuracy; the second type is a direct simulation Monte Carlo method of the particle method, which is low in calculation efficiency but high in accuracy. For the cross-flow field problem that there are continuous flow domains and rarefied flow domains in the flow field, the continuous method and the particle method are difficult to accurately simulate, and therefore a simulation method coupling the continuous / particle on the grid is generated, but this method is mainly applied to the case that there is a clear continuous / rarefied region division in the flow field. SUMMARY

[0004] The application aims to solve the problem in the prior art that the existing simulation method cannot balance the calculation efficiency and the calculation accuracy, and provides a method, system, device and medium for simulating aerodynamic force data of a near-space vehicle.

[0005] To achieve the above object, the application adopts the following technical scheme:

[0006] A method for simulating aerodynamic force data of a near-space vehicle, comprising:

[0007] Step 1: obtaining vehicle shape geometric parameters and gas flow information; based on the obtained vehicle shape geometric parameters and gas flow information, constructing a physical grid of the vehicle;

[0008] Step 2: obtaining macroscopic flux between adjacent physical grids based on a Navier-Stokes solver;

[0009] Step 3: processing particles in the physical grid based on a competition weight mechanism to obtain particles not participating in collision;

[0010] Step 4: Based on the free migration of the non-collision particles, the number of non-collision particles flowing into the adjacent physical grid is counted to obtain the flux of the particle solver;

[0011] Step 5: Based on the macroscopic flux between the adjacent physical grids and the flux of the particle solver, the total interface flux between the adjacent physical grids is obtained;

[0012] Step 6: Based on the total interface flux between the adjacent physical grids, the physical quantity in the physical grid is updated;

[0013] Step 7: Based on the physical quantity in the physical grid, the flow field density is obtained; steps 2 and 6 are regarded as a time step, and steps 2 to 6 are repeated until the flow field density obtained by the adjacent time step is less than the set threshold value;

[0014] Step 8: The simulated flow field and flow characteristic parameters are output.

[0015] Further improvements of the application are as follows:

[0016] Before obtaining the macroscopic flux between the adjacent physical grids, the following steps are further included:

[0017] The initial flow field, state parameters and boundary conditions are set based on the flow characteristics of the gas;

[0018] The flow characteristics of the gas include the type of gas, flow velocity, temperature and density; the state parameters include the corresponding dimensionless velocity, temperature, density, Knudsen number, specific heat ratio and thermal coefficient in the code; and the boundary conditions include the inlet boundary, outlet boundary and solid wall boundary.

[0019] Based on the competition weight mechanism, the particles in the physical grid are processed to obtain the non-collision particles, and the specific steps are as follows:

[0020] Based on the competition weight mechanism, the weight coefficient of the collision particles is obtained;

[0021] Based on the number of particles in the physical grid and the weight coefficient of the collision particles, the number of collision particles in the physical grid is obtained;

[0022] Based on the number of particles in the physical grid and the number of collision particles, the non-collision particles are obtained.

[0023] Based on the competition weight mechanism, the weight coefficient of the collision particles is obtained, and the specific steps are as follows:

[0024]

[0025] Wherein: f is the particle velocity distribution function, g is the equilibrium particle velocity distribution function, x is the particle coordinate, ξ is the particle velocity, c visis a scale-dependent coefficient, f(x, ξ, t) represents a weight coefficient of particle collision and transport; f(x-Δξt, ξ, 0) is a free-migration particle velocity distribution function, is a collision-involved particle velocity distribution function;

[0026] wherein c vis , w free and w hydro are respectively:

[0027]

[0028]

[0029] wherein ω free is a particle solver weight, ω hydro is a Navier-Stokes solver weight, Δt is a time step, and τ is a relaxation time.

[0030] Based on the free migration of the particles not involved in the collision, the number of the particles not involved in the collision flowing into adjacent physical grids is counted to obtain a flux of the particle solver; specifically:

[0031] The adjacent physical grids have an interface; the number of the particles not involved in the collision crossing the interface is counted to obtain the flux of the particle solver.

[0032] The macroscopic flux between the adjacent physical grids and the flux of the particle solver are obtained to obtain an interface total flux between the adjacent physical grids; specifically:

[0033] The macroscopic flux between the adjacent physical grids is multiplied by the weight coefficient of the collision-involved particles, and the obtained result is added to the flux of the particle solver to obtain the interface total flux between the adjacent physical grids.

[0034] Flow field densities between adjacent time steps; specifically:

[0035] S1: Obtain flow field densities of n time steps and flow field densities of n+1 time steps, sum the flow field densities of n time steps and the flow field densities of n+1 time steps and take an average value;

[0036] S2: Obtain flow field densities of n+2 time steps, sum the flow field densities of n time steps, the flow field densities of n+1 time steps and the flow field densities of n+2 time steps and take an average value;

[0037] S3: Obtain flow field densities of n+3 time steps, sum the flow field densities of n time steps, the flow field densities of n+1 time steps, the flow field densities of n+2 time steps and the flow field densities of n+3 time steps and take an average value;

[0038] Continuously repeat the time step until the average value obtained is less than the set threshold value; wherein the value of n is artificially selected.

[0039] A system for simulating aerodynamic force data of a near space vehicle, comprising:

[0040] A construction module for obtaining vehicle shape geometric parameters and gas flow information; and constructing a physical grid of the vehicle based on the obtained vehicle shape geometric parameters and gas flow information;

[0041] A first obtaining module for obtaining macroscopic fluxes between adjacent physical grids based on a Navier-Stokes solver;

[0042] A second obtaining module for processing particles in the physical grid based on a competition weight mechanism to obtain non-collision particles;

[0043] A third obtaining module for counting the number of non-collision particles flowing into adjacent physical grids based on the free migration of non-collision particles to obtain fluxes of a particle solver;

[0044] A fourth obtaining module for obtaining total fluxes between adjacent physical grids based on the macroscopic fluxes between adjacent physical grids and the fluxes of the particle solver;

[0045] An updating module for updating physical quantities in the physical grid based on the total fluxes between adjacent physical grids;

[0046] A judging module for obtaining a flow field density based on the physical quantities in the physical grid; and until the flow field density obtained at an adjacent time step is less than a set threshold value;

[0047] An output module for outputting a simulated flow field and flow characteristic parameters.

[0048] A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0049] A computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement the steps of the above method.

[0050] Compared with the prior art, the present application has the following beneficial effects:

[0051] The application obtains the particles not participating in the collision in the physical grid through the competition weight mechanism, and counts the number of the particles not participating in the collision flowing into the adjacent physical grid to obtain the flux of the particle solver; based on the macro flux between the adjacent physical grids and the flux of the particle solver, the total flux between the adjacent physical grids is obtained; the physical quantity in the physical grid is updated, and the flow field density is obtained based on the physical quantity in the physical grid; whether the flow field density obtained at the adjacent time step is less than the set threshold value is judged; if yes, the simulated flow field and the flow characteristic parameter are output. The application accurately simulates the cross-flow domain flow problem existing in the flow field of the near space vehicle, simulates the aerodynamic shape of the near space vehicle and obtains the aerodynamic force data of the near space vehicle, solves the problem that the existing simulation method cannot consider the calculation efficiency and the calculation accuracy, and reduces the memory occupation and improves the calculation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical scheme in the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation to the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0053] Figure 1 The flow chart of the method for simulating the aerodynamic force data of the near space vehicle of the application;

[0054] Figure 2 The system structure diagram of the method for simulating the aerodynamic force data of the near space vehicle of the application;

[0055] Figure 3 The physical grid schematic diagram of the hypersonic blunt cone; wherein, (a) is the physical grid of the outer surface of the hypersonic blunt cone; (b) is the internal physical grid of the hypersonic blunt cone;

[0056] Figure 4 The surface coefficient comparison diagram of the hypersonic blunt cone; wherein, (a) is the surface pressure coefficient schematic diagram of the hypersonic blunt cone; (b) is the surface friction coefficient diagram of the hypersonic blunt cone; (c) is the surface heat flow coefficient diagram of the hypersonic blunt cone;

[0057] Figure 5 The surface calculation result diagram of the hypersonic blunt cone; wherein, (a) is the surface pressure coefficient distribution schematic diagram of the hypersonic blunt cone; (b) is the surface heat flow coefficient distribution diagram of the hypersonic blunt cone;

[0058] Figure 6 The flow field temperature cloud diagram of the hypersonic blunt cone; wherein, (a) is the total temperature schematic diagram of the flow field of the hypersonic blunt cone; (b) is the translation temperature schematic diagram of the flow field of the hypersonic blunt cone; (c) is the rotation temperature schematic diagram of the flow field of the hypersonic blunt cone. DETAILED DESCRIPTION

[0059] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some but not all of the embodiments of the present application. Generally, the components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative work fall within the scope of protection of the present application.

[0061] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0062] In the description of the embodiments of the present application, it should be noted that, if the orientation or position relationship indicated by the terms "upper", "lower", "horizontal", "inner" and the like is based on the orientation or position relationship shown in the drawings, or is the orientation or position relationship when the product of the present application is usually placed, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, therefore, it cannot be understood as a limitation on the present application. In addition, the terms "first", "second" and the like are only used for differentiation in description, and cannot be understood as indicating or implying relative importance.

[0063] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly inclined. For example, "horizontal" only means that its direction is relatively more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly inclined.

[0064] In the description of the embodiments of the present application, it should also be noted that, unless otherwise explicitly specified and limited, if the terms "arrange", "mount", "connect", "connect" appear, they should be understood in a broad sense, for example, can be fixedly connected, can be detachably connected, or integrally connected; can be mechanically connected, can be electrically connected; can be directly connected, can be indirectly connected through an intermediate medium, can be the communication inside two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0065] The application will be described in further detail below with reference to the drawings:

[0066] Referring to Figure 1 The application discloses a method for simulating aerodynamic force data of a near-space vehicle, comprising the following steps:

[0067] S101: acquiring vehicle shape geometric parameters and gas flow information; and constructing a physical grid of the vehicle based on the acquired vehicle shape geometric parameters and gas flow information;

[0068] S102: acquiring macroscopic flux between adjacent physical grids based on a Navier-Stokes solver;

[0069] Before acquiring the macroscopic flux between the adjacent physical grids, the method further comprises the following steps:

[0070] setting an initial flow field, state parameters and boundary conditions based on flow characteristics of the gas;

[0071] The flow characteristics of the gas include gas types, flow velocities, temperatures and densities; the state parameters include corresponding dimensionless velocities, temperatures, densities, Knudsen numbers, specific heat ratios and thermal coefficients in the code; and the boundary conditions include inlet boundaries, outlet boundaries and solid wall boundaries.

[0072] S103: processing particles in the physical grid based on a competition weight mechanism to acquire particles not participating in collision.

[0073] S103.1: acquiring a weight coefficient of the particles participating in collision based on the competition weight mechanism;

[0074] S103.2: acquiring the number of the particles participating in collision in the physical grid based on the number of the particles in the physical grid and the weight coefficient of the particles participating in collision;

[0075] S103.3: acquiring the particles not participating in collision based on the number of the particles in the physical grid and the number of the particles participating in collision.

[0076] The weight coefficient of the particles participating in collision is acquired based on the competition weight mechanism, and the weight coefficient is specifically acquired as follows:

[0077]

[0078] Wherein, f is a particle velocity distribution function, g is an equilibrium particle velocity distribution function, x is a particle coordinate, ξ is a particle velocity, c vis is a scale correlation coefficient, f(x, ξ, t) represents a weight coefficient of collision and transportation of the particles; f(x-Δξt, ξ, 0) is a free migration particle velocity distribution function, is a particle velocity distribution function participating in collision;

[0079] Wherein, c vis, w free and w hydro are respectively:

[0080]

[0081]

[0082] where ω free is the particle solver weight, ω hydro is the Navier-Stokes solver weight, Δt is the time step, and τ is the relaxation time.

[0083] S104: Based on the free migration of the non-collision particles, the number of non-collision particles flowing into the adjacent physical grid is counted to obtain the flux of the particle solver;

[0084] There is an interface between adjacent physical grids; the number of non-collision particles crossing the interface is counted to obtain the flux of the particle solver.

[0085] S105: Based on the macroscopic flux between adjacent physical grids and the flux of the particle solver, the total interface flux between adjacent physical grids is obtained.

[0086] The macroscopic flux between adjacent physical grids is multiplied by the collision particle weight coefficient, and the obtained result is added to the flux of the particle solver to obtain the total interface flux between adjacent physical grids.

[0087] S106: Based on the total interface flux between adjacent physical grids, the physical quantity in the physical grid is updated.

[0088] In computational fluid dynamics, flux represents the physical quantity flowing into and out of the grid, and the macroscopic quantity in the physical grid can be updated by adding or subtracting the interface flux according to the direction of the flux.

[0089] S107: Based on the physical quantity in the physical grid, the flow field density is obtained; S102 and S106 are regarded as one time step, and S102 to S106 are repeated until the flow field density obtained between adjacent time steps is less than the set threshold value;

[0090] The flow field density between adjacent time steps; specifically:

[0091] S1: Obtain the flow field density of n time step and the flow field density of n+1 time step, sum the flow field density of n time step and the flow field density of n+1 time step and take the average value;

[0092] S2: Obtain the flow field density of n+2 time step, sum the flow field density of n time step, the flow field density of n+1 time step and the flow field density of n+2 time step, and take the average value;

[0093] S3: obtaining the flow field density of the n+3 time step, summing and averaging the flow field density of the n time step, the flow field density of the n+1 time step, the flow field density of the n+2 time step and the flow field density of the n+3 time step;

[0094] The time step is repeatedly performed until the obtained average value is less than the set threshold value; wherein the value of n is artificially selected.

[0095] S108: outputting the simulated flow field and the flow characteristic parameter.

[0096] Referring to Figure 2 , the application discloses a system for simulating aerodynamic force data of a near-space vehicle, comprising:

[0097] A construction module is configured to obtain vehicle shape geometric parameters and gas flow information, and construct a physical grid of the vehicle based on the obtained vehicle shape geometric parameters and gas flow information.

[0098] A first obtaining module is configured to obtain macroscopic fluxes between adjacent physical grids based on a Navier-Stokes solver.

[0099] A second obtaining module is configured to process particles in the physical grid based on a competition weight mechanism, and obtain non-collision particles.

[0100] A third obtaining module is configured to count the number of non-collision particles flowing into adjacent physical grids based on the free migration of the non-collision particles, and obtain fluxes of a particle solver.

[0101] A fourth obtaining module is configured to obtain interface total fluxes between adjacent physical grids based on the macroscopic fluxes between the adjacent physical grids and the fluxes of the particle solver.

[0102] An updating module is configured to update physical quantities in the physical grid based on the interface total fluxes between the adjacent physical grids.

[0103] A judging module is configured to obtain a flow field density based on the physical quantities in the physical grid; until the flow field density obtained at an adjacent time step is less than a set threshold value.

[0104] An output module is configured to output a simulated flow field and a flow characteristic parameter.

[0105] Embodiment one: a hypersonic blunt cone example

[0106] 1. Obtain vehicle shape geometric parameters and gas flow information; based on the obtained vehicle shape geometric parameters and gas flow information, construct a physical grid of the vehicle. The physical grid is as shown inFigure 3 The results are shown in the following table.

[0107] 2. Set initial flow field, state parameters and boundary conditions according to flow characteristics. Test conditions are shown in Table 1.

[0108] Table 1. Calculated inflow conditions

[0109] Test gas Nitrogen Inflow temperature 143.5K Wall temperature 600K Mach number (Ma) 10.15 Reynolds number (Re) 232.8 Angle of attack (AOA) 0 Rotational collision number 4.2

[0110] 3. Obtain macroscopic flux between adjacent physical grids based on Navier-Stokes solver.

[0111] 4. Process particles in the physical grid based on competition weight mechanism to obtain particles not participating in collision.

[0112] 5. Based on free migration of particles not participating in collision, count the number of particles not participating in collision flowing into adjacent physical grids to obtain flux of particle solver.

[0113] 6. Obtain total flux between adjacent physical grids based on macroscopic flux between adjacent physical grids and flux of particle solver.

[0114] 7. Update physical quantities in the physical grid based on total flux between adjacent physical grids.

[0115] 8. Obtain flow field density based on physical quantities in the physical grid; take step 3 and step 7 as one time step, repeat step 3 to step 7 until the flow field density obtained in adjacent time steps is less than a set threshold.

[0116] 9. Output simulated flow field and flow characteristic parameters.

[0117] Reference is made to Figure 4 , Figure 5 and Figure 6 It can be seen that the current calculation result is in good agreement with the reference result, verifying the correctness of the method.

[0118] The terminal device provided by the embodiment of the application. The terminal device of the embodiment includes a processor, a memory, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the steps in each of the method embodiments described above. Alternatively, the processor executes the computer program to implement the functions of each module / unit in each of the device embodiments described above.

[0119] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the application.

[0120] The terminal device can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The terminal device can include, but is not limited to, a processor and a memory.

[0121] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like.

[0122] The memory can be used to store the computer program and / or modules, and the processor can realize various functions of the terminal device by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory.

[0123] The modules / units integrated in the terminal device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer-readable storage medium. When the processor executes the computer program, the steps of the above-mentioned various method embodiments can be realized. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution medium, etc. It should be noted that the contents included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0124] The above merely describes the preferred embodiments of the present application, and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for simulating aerodynamic data of near-space vehicles, characterized in that, include: Step 1: Obtain the aircraft's external geometry parameters and gas flow information; based on the obtained aircraft external geometry parameters and gas flow information, construct the aircraft's physical mesh; Step 2: Obtain the macroscopic flux between adjacent physical grids based on the Navier-Stokes solver; Step 3: Based on the competitive weight mechanism, process the particles in the physical grid to obtain particles that did not participate in the collision; specifically: Based on the competitive weighting mechanism, obtain the weight coefficients of the particles participating in the collision. （1） in: Let be the particle velocity distribution function. Let be the equilibrium particle velocity distribution function. For particle coordinates, For particle velocity, The scale correlation coefficient, The weighting coefficients representing the collision and transport of particles; Let be the velocity distribution function of freely migrating particles. The velocity distribution function of the colliding particles; in, , and They are respectively: （2） （3） Where, ω free For the particle solver weights, ω hydro Here, Δt represents the weights of the Navier-Stokes solver, τ represents the time step, and τ represents the relaxation time. The number of particles participating in collisions in the physical grid is obtained based on the number of particles in the physical grid and the weight coefficients of the particles participating in the collision. Based on the number of particles in the physical grid and the number of particles that participated in the collision, obtain the particles that did not participate in the collision. Step 4: Based on the free migration of particles that do not participate in collisions, count the number of particles that do not participate in collisions flowing into adjacent physical grids to obtain the flux of the particle solver; Specifically: There are interfaces between the adjacent physical grids; the number of non-collision particles that cross the interfaces is counted to obtain the flux of the particle solver. Step 5: Based on the macroscopic flux between adjacent physical grids and the flux of the particle solver, obtain the total interface flux between adjacent physical grids; Specifically: The total interface flux between adjacent physical grids is obtained by multiplying the macroscopic flux between adjacent physical grids by the weight coefficients of the colliding particles and adding the result to the flux of the particle solver. Step 6: Update the physical quantities in the physical grid based on the total flux at the interface between adjacent physical grids; Step 7: Obtain the flow field density based on the physical quantities in the physical grid; treat Step 2 and Step 6 as one time step, and repeat Step 2 to Step 6 until the flow field density obtained in adjacent time steps is less than the set threshold. The flow field density between adjacent time steps; specifically: S1: Obtain the flow field density at time step n and time step n+1, sum the flow field density at time step n and time step n+1 and take the average value. S2: Obtain the flow field density at time step n+2, sum the flow field densities at time step n, time step n+1, and time step n+2, and take the average value. S3: Obtain the flow field density at time step n+3, sum the flow field densities at time step n, time step n+1, time step n+2, and time step n+3, and take the average value. Repeat the time steps until the calculated average value is less than the set threshold; where the value of n is manually selected. Step 8: Output the simulated flow field and flow characteristic parameters.

2. The method for simulating aerodynamic data of near-space vehicles according to claim 1, characterized in that, Before obtaining the macroscopic flux between adjacent physical grids, the following is also included: The initial flow field, state parameters, and boundary conditions are set based on the gas flow characteristics. The gas flow characteristics include gas type, flow velocity, temperature and density; the state parameters include the dimensionless velocity, temperature, density, Knudsen number, specific heat ratio and thermal coefficient corresponding to the code; the boundary conditions include inlet boundary, outlet boundary and solid wall boundary.

3. A system for simulating aerodynamic data of near-space vehicles, based on the method for simulating aerodynamic data of near-space vehicles as described in claim 1, characterized in that, include: A construction module is used to acquire the aircraft's external geometric parameters and gas flow information; and to construct the aircraft's physical mesh based on the acquired external geometric parameters and gas flow information. The first acquisition module, based on the Navier-Stokes solver, acquires the macroscopic flux between adjacent physical grids; The second acquisition module processes the particles in the physical grid based on a competitive weight mechanism to acquire particles that have not participated in the collision. The third acquisition module, based on the free migration of particles that do not participate in collisions, counts the number of particles that do not participate in collisions flowing into adjacent physical grids and obtains the flux of the particle solver. The fourth acquisition module acquires the total interface flux between adjacent physical grids based on the macroscopic flux between adjacent physical grids and the flux of the particle solver. The update module updates the physical quantities in the physical grid based on the total flux of the interface between adjacent physical grids; The judgment module obtains the flow field density based on physical quantities in the physical grid; until the flow field density obtained in the adjacent time step is less than the set threshold. The output module is used to output the simulated flow field and flow characteristic parameters.

4. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-2.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-2.

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